The person would be working at the intersection of cloud infrastructure and AI/LLM engineering — specifically:
- Designing and deploying AI agents using Google’s Gemini models
- Using GCP’s Vertex AI as the primary ML platform (model hosting, pipelines, endpoints)
- Building with Google’s agent tooling — the Agent Development Kit (ADK) for constructing agent logic, and the Managed Agents API for running/orchestrating them at scale
- Likely involved in things like tool-calling, multi-agent orchestration, RAG pipelines, and connecting agents to enterprise systems
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Role Responsibilities
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Architecting and implementing infrastructure as code (IaC) .
- Defining administrative choices for environments that are auto-configured by IaC.
- Focus on agent use cases , including relationships with BigQuery databases, enterprise connectors, and agent orchestration.
- Heavy leverage of Vertex .
- Investigating and tweaking designs to avoid issues with Pfizer’s enterprise infrastructure and GCP limitations.
Requirements
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Required Skills and Experience
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Strong background in GCP and Vertex .
- Experience with IaC technologies like Kubernetes, Terraform, and CI/CD.
- Enterprise environment experience is crucial to navigate existing GCP and ISRM teams and strictures.
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Preferred transferable skills (due to rarity of specific Google ADK experience):
- Mature experience in AWS or Azure .
- Experience with Bedrock or Azure Agent Foundry .
- GCP experience combined with LangGraph or LangChain .
Originally posted on Himalayas